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TargetModel in python bindings #1500

Merged
merged 7 commits into from
May 21, 2024
Merged

TargetModel in python bindings #1500

merged 7 commits into from
May 21, 2024

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fifield
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@fifield fifield commented May 17, 2024

I thought it would be useful to query TargetModel from python, for things like L1 size and number of columns.

>>> from aie.dialects.aie import AIEDevice, get_target_model
>>> get_target_model(AIEDevice.npu1_3col).columns()
3

@makslevental this has some overlap with PybindTypes.cpp used in the python pass stuff, so ultimately maybe there is a better way to do this. But this is one way I found to make it work.

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Awesome! I've been wanting this!

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makslevental commented May 18, 2024

You can't do this. Well you can't do this and not run afoul of the RTTI constraints imposed by IREE and such - namely that there be no RTTI anywhere except the bindings modules. Lest you imagine that that is what you have here, I encourage you to try to build in no_rtti mode as we do here https://github.com/Xilinx/mlir-aie/blob/main/.github/workflows/mlirAIEDistro.yml#L103.

You also can't do this because you're not actually linking the dialect libs and either getting lucky that the right code ends up in the AggregateCAPI lib or not (currently the tests fail).

Much more information here and here.

In summary: there's a reason why the PybindTypes stuff is behind a build flag and also the CMake around there is "black magic".

EDIT:

Indeed the fails are due to missing symbols

ImportError: /home/runner/work/mlir-aie/mlir-aie/build_assert/python/aie/_mlir_libs/_aie.cpython-38-x86_64-linux-gnu.so:
 undefined symbol: _ZTVN6xilinx3AIE14AIETargetModelE
FileCheck error: '<stdin>' is empty.

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You can't do this. Well you can't do this and not run afoul of the RTTI constraints imposed by IREE and such - namely that there be no RTTI anywhere except the bindings modules. Lest you imagine that that is what you have here, I encourage you to try to build in no_rtti mode as we do here https://github.com/Xilinx/mlir-aie/blob/main/.github/workflows/mlirAIEDistro.yml#L103.

You also can't do this because you're not actually linking the dialect libs and either getting lucky that the right code ends up in the AggregateCAPI lib or not (currently the tests fail).

Much more information here and here.

In summary: there's a reason why the PybindTypes stuff is behind a build flag and also the CMake around there is "black magic".

EDIT:

Indeed the fails are due to missing symbols

ImportError: /home/runner/work/mlir-aie/mlir-aie/build_assert/python/aie/_mlir_libs/_aie.cpython-38-x86_64-linux-gnu.so:
 undefined symbol: _ZTVN6xilinx3AIE14AIETargetModelE
FileCheck error: '<stdin>' is empty.

Is there a better way to do this that you can suggest @makslevental ?

@fifield fifield force-pushed the py_target_model branch 2 times, most recently from 8adf5af to c827a7d Compare May 20, 2024 19:07
@makslevental
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Is there a better way to do this that you can suggest @makslevental ?

Jeff got it - you just have to plumb everything through a C API.

@fifield fifield force-pushed the py_target_model branch from e5f8921 to 4ef51b6 Compare May 21, 2024 02:59
@fifield fifield enabled auto-merge May 21, 2024 02:59
@fifield fifield added this pull request to the merge queue May 21, 2024
Merged via the queue into Xilinx:main with commit 66e642b May 21, 2024
51 checks passed
@fifield fifield deleted the py_target_model branch May 21, 2024 03:49
@@ -54,7 +54,7 @@ using TileID = struct TileID {

class AIETargetModel {
public:
AIETargetModel() = default;
AIETargetModel(AIEDevice device) : device(device) {}
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I think this is not a good idea... My intention with the TargetModel is that it's a singleton pattern, which is independent of the MLIR. an AIEDevice is the device of a particular design. And a Device is not actually necessary, only a container object that implements the right interface. It's unclear to me why you need to walk from the TargetModel back to a device anyway?

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It was convenient for wrapping/unwrapping to keep only the enum around, and this helped with that. https://github.com/Xilinx/mlir-aie/pull/1500/files#diff-3f51e6951752378031f1f22e2616b9d3c77de3a54fcbb31cdc6ab6bd34d109dbR18-R24. But I can probably refactor to avoid the change to TargetModel

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4 participants